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8/3/2019 Sajjad FIT'11
1/22
MCDM Method and Semantics Integration forUnified Communication Management and Control
Sajjad Ali Musthaq, Christophe Lohr, Annie Gravey
Department of Computer Engineering
Telecom Bretagne Brest, France
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Motivations
- Which access provides the bestQoS with least cost?
FIT 2011, Islamabad Pakistan
Project Stackholder:
Partners: Alcatel, Comverse and Telecom Bretagne
Company m@ges
Company m@ges
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Introduction We are at frontiers between
private-public network border How to manage ressources
in multi-service, multi-vendorsand multi-homedenvironnement ?
Traffic management issues atthe private-public border.
Call Server and Session BorderController are the mainelements.
FIT 2011, Islamabad Pakistan
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Outlines
FIT 2011, Islamabad Pakistan
Proposed Architecture
Multi Criteria Decision Making (MCDM)
Grey Relational Analysis (GRA) and its Application Over
the Proposed Platform System Model Regarding the Problem
Ontology Integration with MCDM.
Test Bed for the Validation of the Proposed Solution.
Conclusion
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Proposed
Architecture
-Call Server-Handles registration,user profile and servicemanagement.-Performs profile related
CAC
-Session Border Controller-Performs NAT/PATtranslation-Handles ressources related
CAC-Analyzes SIP/SDP-Acts as PolicyEnforcement Point(PEP)
FIT 2011, Islamabad Pakistan
Control Plane
SBC
Mobile operator
3G
Call Server
SDSL router
ADSL router
ADSL router(limited)
Operator Hot Spot3G
FAI1
Policy server
DSLAM
DSLAM
DSLAM
SIP/IP flow
SNMP flow
Data traffic
MONA sub-project
VPN SIP Client
SIP client
Service plane
Proxy/FW
Reverse proxy
SIP client
SIP client
Application data traffic
(HTTP, SNMP, streaming HTTP, proprietary )
SIP/media
Network/Transport plane
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Proposed Architecture
-We have introduced PolicyServer (PS)-Decision Engine within PSprovides dynamic/efficient
control and managementWhile taking into accountdynamic and static info
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Proposed Architecture
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Goals, Criteria, Objectives
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Multi Criteria Decision Making (MCDM)
Problems of decision making might involvemultiple objectives and goals. For example:
Locating a nuclear power plant involves objectives such as:
- Safety
- Health
- Environment
- Cost
- FaultLine (Evolution after Japan Incident)
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Multi Criteria Decision Making (MCDM) and the
Decision Engine
Several Criteria Link Profiles
User Profiles
Business Objectives
Attributes extracted from the context
A Multi-criteria, Multi-Attribute and Multi-objective
problem has to be addressed.
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MCDM Method Application
Figuring out the Goals, Criteria, And Alternatives.
Hierarchy Construction
Decision Matrix
Utility Function
Mathematical Steps
to rank/grade the links
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Grey Relational Analysis Method
Reference Vector (Link benchmark) construction from
context and platform conditions
Normalization of the Decision Matrix
Normalization of the Reference Vector (RV) Finding the distance between the corresponding entities in
DM and RV
Calculating Grey Relational Coefficients (GRC)s
Finding the weights of the Criteria elementsWeighted normalized GRC matrix
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Inter/ Intra Plane Semantics, Variations
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Ontology
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Service Profile
Voice
Service
Video
Service
Service
Parameter
Operational
Parameter
Service-specific
Parameter
QoSAttribute
Measurable
Attribute
Physical
Attribute
Metric Unit
SLA Service
Provider
QoS
MetricViolation Availability Reliability Charging
Methodology
Threshold Aggregation Performance
Bandwidth Physical
supportssupports
offers
Service Ontology
QoS Ontology
SLA Ontology Model
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Modules of Policy Server Framework
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Test Bed to Validate the Solution
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Application Of GRA Over the Test Bed
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UR Utilization Ratio
D Delay
J Jitter
PL Packet Loss
TB Total Bandwidth
AB AvailableBandwidth
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Observations (Throughput)
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Higher throughput
Better resource utilization
1 2 3 40
1
2
3
4
5
6
7
8
9
10x 10 7
Links
B
its/s
Total Capacity of Each Link in Bits/s
Throughput W ithout Decis ion Engine
Throughput W ith De cis ion Eng ine
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Observations (Call Dropping Probability)
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Lower call dropping
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Observations (Delay)
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The cost of the rise in throughput and decrease in CDP is an add-on
delay
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Conclusions
The proposed decision engine accommodates multiple
goals, criteria, sub criteria and alternatives.
Dynamic variations and fluctuations are being taken into
account while computing decision.
Semantics are being captured by integrating Ontology
with MCDM.
The system offers better throughput with an add-on delay
Call Dropping Probability (CDP) for routing decisions
computed via the system is lower than the built-in Load
Balancer (LB).
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Thank YouFor Questions please contact
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